1. Personality, 9e Jerry M. Burger
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2. Personality Research Methods
Chapter 2
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3. Chapter Outlines Hypothesis-testing approach Case study method
Statistical analysis of data
Personality assessment
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4. Hypothesis-Testing Approach
Theory: General statement about the relationship between constructs or events
Differ in the range of events or phenomena they explain
Characteristics of a good theory
Parsimonious - Explains the phenomenon in simple terms
Useful - Generates testable hypothesis
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5. Hypothesis-Testing Approach
Hypothesis: Formal prediction about the relationship between two or more variables that is logically derived from the theory
A theory is unaccepted if empirical investigations consistently fail to confirm predictions
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6. Figure 2.1 - Example of the Hypothesis-Testing Approach
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7. Types of Experimental Variables
Independent: Determines how the groups in the experiment are divided
Is manipulated by the experimenter
Known as treatment variable
Dependent: Measured by the investigator and used to compare the experimental groups
Known as outcome variable
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8. Interaction of Experimental Variables
How one independent variable affects the dependent variable depends on the other independent variable
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9. Manipulated Versus Nonmanipulated Independent Variables
Begins with a large number of participants
Randomly assigns participants to experimental groups
Researchers assume that all the differences will be evened out
Exists without the researcher’s intervention
Investigator does not randomly assign participants to a condition
Researcher cannot assume the people in the two groups are identical
Difficult to find cause-and-effect relationships
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10. Prediction Versus Hindsight
Accurate predictions can be made if a scientist has a legitimate theory
Purpose of research is to provide support for a hypothesis
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11. Prediction Versus Hindsight
Researchers:
Generate a theory
Make a hypothesis
Collect data that supports or opposes hypothesis
Unpredicted findings by the researchers are the basis for future hypotheses and research
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12. Replication
Examines participant populations different from those used in the original research
Helps to determine whether the effect applies to larger number of people or is limited to the kind of individuals used in the original sample
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13. Replication
Determining the strength of an effect by how often it is replicated is difficult
File Drawer problem
Investigators publish and report research only when they find significant effects
Failed attempt at replication makes researcher to decide something has gone wrong
Leads research being stored in a file drawer and never reported
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14. Case Study Method In-depth evaluation of individuals
Participant is a psychotherapy client suffering from a problem that interests the investigator
Researcher records in detail:
Person’s history
Current behavior
Changes in behavior
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15. Case Study Data are usually descriptive
Psychologists rely on in-depth analysis of the patients while formulating ideas about personality
Helped behaviorists to illustrate:
Various aspects of their theories
Effectiveness of their therapies
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16. Limitations of Case Study Method
Generalizing from a single individual to other people
Determining cause-and-effect relationships with the case study method
Interference of investigator's subjective judgments with scientific objectivity
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17. Strengths of the Case Study Method
Offers insight into the richness of a person's life
Valuable for generating hypotheses about the nature of human personality
Acts as a useful research tool
Appropriate in examining a rare case
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18. Strengths of the Case Study Method
Suitable for arguing that the individual being studied is normal on the dimensions of interest
Illustrates a treatment
Demonstrates possibilities
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19. Statistical Analysis of Data
Types of statistical tests appropriate for different types of data and research designs
Analysis of variance
Chi-square test
Correlation coefficient
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20. Statistical Analysis of Data
Statistical significance
The difference between two averages is large enough to consider that it was not caused by chance but reflects a true difference between two observations
Size of the difference is indicated through statistical values known as effect size indicators
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21. Statistical Analysis of Data
Correlation coefficients
Statistical test that helps understand the relationship between two measures
Statistical data is reduced to a single number that ranges from 1.00 to -1.00
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22. Figure 2.3 - Three Possible Relations Between Loneliness and Depression
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23. Reliability Extent to which a test measures consistently
Determined by calculating test-retest reliability coefficient
Factors contributing to poor consistency
Vague test questions or scoring procedures
Fluctuation in response due to taker’s mood
Internal consistency
All items on the test measure the same thing
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24. Reliability Internal consistency coefficient
High coefficient indicates that most of the items are measuring the same concept
Low coefficient suggests items are measuring more than one concept
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25. Validity
Extent to which a test measures what it is designed to measure
Easy to determine for some kinds of tests
Face validity
Way to decide whether a test measures what it says it measures is to look at the test items
Less certain than with more straightforward measures
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26. Validity Congruent validity Discriminant validity
Extent to which scores from the test correlate with other measures of the same construct
Otherwise known as convergent validity
Discriminant validity
Extent to which a test score does not correlate with the scores of theoretically unrelated measures
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27. Validity Behavioral validation
Step in determining the construct validity of a test
Test scores predicting relevant behavior is important
Usefulness of the test must be questioned if test scores cannot predict behavior
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